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davanstrien
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flyswot_iiif

Image Classification
Transformers
PyTorch
convnext
Generated from Trainer
Inference Endpoints
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+ ---
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - f1
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+ model-index:
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+ - name: flyswot_iiif
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # flyswot_iiif
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+
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+ This model is a fine-tuned version of [facebook/convnext-base-224-22k](https://huggingface.co/facebook/convnext-base-224-22k) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 6.1280
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+ - F1: 0.0034
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 64
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+ - eval_batch_size: 64
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+ - seed: 666
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 8
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+ - mixed_precision_training: Native AMP
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+ - label_smoothing_factor: 0.1
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|
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+ | 8.5184 | 0.26 | 500 | 7.9280 | 0.0005 |
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+ | 7.7409 | 0.52 | 1000 | 7.5824 | 0.0007 |
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+ | 7.4649 | 0.78 | 1500 | 7.3841 | 0.0010 |
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+ | 7.3285 | 1.04 | 2000 | 7.2652 | 0.0012 |
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+ | 7.1404 | 1.3 | 2500 | 7.1559 | 0.0014 |
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+ | 7.0322 | 1.56 | 3000 | 7.0551 | 0.0016 |
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+ | 6.9197 | 1.82 | 3500 | 6.9449 | 0.0019 |
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+ | 6.7822 | 2.09 | 4000 | 6.8773 | 0.0018 |
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+ | 6.6506 | 2.35 | 4500 | 6.7980 | 0.0020 |
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+ | 6.5811 | 2.61 | 5000 | 6.7382 | 0.0022 |
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+ | 6.538 | 2.87 | 5500 | 6.6582 | 0.0022 |
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+ | 6.4136 | 3.13 | 6000 | 6.6013 | 0.0024 |
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+ | 6.3325 | 3.39 | 6500 | 6.5369 | 0.0024 |
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+ | 6.2566 | 3.65 | 7000 | 6.4875 | 0.0025 |
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+ | 6.2285 | 3.91 | 7500 | 6.4342 | 0.0027 |
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+ | 6.1281 | 4.17 | 8000 | 6.4066 | 0.0027 |
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+ | 6.0762 | 4.43 | 8500 | 6.3674 | 0.0027 |
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+ | 6.0309 | 4.69 | 9000 | 6.3336 | 0.0027 |
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+ | 6.0123 | 4.95 | 9500 | 6.2932 | 0.0030 |
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+ | 5.9089 | 5.21 | 10000 | 6.2835 | 0.0029 |
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+ | 5.8901 | 5.47 | 10500 | 6.2481 | 0.0030 |
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+ | 5.86 | 5.74 | 11000 | 6.2295 | 0.0030 |
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+ | 5.8586 | 6.0 | 11500 | 6.2068 | 0.0033 |
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+ | 5.7768 | 6.26 | 12000 | 6.1937 | 0.0031 |
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+ | 5.7591 | 6.52 | 12500 | 6.1916 | 0.0032 |
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+ | 5.7443 | 6.78 | 13000 | 6.1579 | 0.0033 |
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+ | 5.7125 | 7.04 | 13500 | 6.1478 | 0.0033 |
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+ | 5.6751 | 7.3 | 14000 | 6.1379 | 0.0035 |
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+ | 5.6648 | 7.56 | 14500 | 6.1304 | 0.0035 |
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+ | 5.6644 | 7.82 | 15000 | 6.1280 | 0.0034 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.17.0.dev0
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+ - Pytorch 1.10.0+cu111
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+ - Datasets 1.18.3
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+ - Tokenizers 0.11.6